Monthly Archives: August 2017

Of the many lessons that we learned in the aftermath of the Great Recession of 2008, one of the most glaring is the persistent gap between the so-called “haves” and “have-nots.” While that gap is true on an individual level, it is also true in a geographical sense.

Since New York legalized boxing in 1896, it became one of the most popular sports in the United States. Due to a great number of immigrants arriving in the United States from all over the world, the country was home to one of the most exciting boxing platforms ever. A great constellation of talented boxers from Ireland, Great Britain, Germany, Scandinavia, Central and Western Europe became popular and well-recognized after arriving in America. In the beginning of the 20th century, boxing became not only one of the shortest paths to glory and financial wealth but also a way to avoid poverty and hunger and provide food for the fighters’ families. There was a time when Jack Dempsey and Joe Louis were national heroes and role models for entire generations.

Exploring utility patents is not an easy task. The system that is currently in place, Cooperative Patent Classification, has its issues. For example, many patent applications have multiple classifications only partially related to the invention itself. This proves useful if you are searching for something specific — on the other hand, it is not as helpful if you are interested in patent mining or visualization.

Luckily, one can easily accomplish most of these tasks with the help of advanced computational techniques. The most promising approach is the use of Natural Language Processing to classify and visualize patents based on their abstracts.

According to the statistics, over 230 million people worldwide suffer from asthma. The prevalence of asthma in the United States has steadily increased to its current level of 8.6 percent. In comparison, this rate was only 7.6 percent in 2001. The percentage of people diagnosed with asthma began to grow in 2013 (7.4 percent). In 2014 and 2015, the rates of people suffering from asthma were amounted to 7.9 percent and 8 percent accordingly.

In 2013, advocates of gender equality celebrated two important anniversaries: 50 years of both the Equal Pay Act and Betty Friedan’s “The Feminine Mystique,” which marked the beginning of second-wave feminism in the United States in the 1960s. After 50 years of revolutionary changes, achievements in gender equality leave us with mixed feelings. As our brief statistical overview will later show, women have come a long way; today, more women are working, and fewer are getting married.

As we continue to explore the U.S. Census Bureau County Business Patterns data, we take a look at the fastest-growing industries. To visualize the dynamics, we plotted the relative change of job numbers from 2000 through 2012. The following figure contains the data for all industries employing at least 5 million people, starting from 100 percent in 2000.

Nowadays, technology and people are so strongly connected that you can hardly imagine life without it. The Internet became an important instrument for everyone and for everything, whether it is studying, working, entertainment or more. The number of computer users in the world, and America in particular, is growing at a quick rate, so let’s figure out who they actually are.

We have already looked into the changes in regional business profiles in the Southern and Midwestern United States. Today, we focus on studying the changes in the most recent County Business Patterns data in the western states and find out which is the fastest-growing sector.

In this post, we continue to study self-assessed health levels in the U.S. Once again, we’ll use the Health Index we introduced in a previous post. Today’s discussion will mostly focus on the relationship between health and income level.

In the aforementioned post, we already saw that health levels decline with age. On the other hand, income levels are generally positively correlated with age, so it’s not obvious from the start how income levels would affect health. Let’s see for ourselves: